img.axs[0][i].text(0.05, 0.95, "$10^2 m_1 = %.3f \pm %.3f$"%(100*(mc[i,2]-1),100*mc[i,3]), color='green', ha='left',
va='center', transform=img.axs[0][i].transAxes, fontsize=18)
img.axs[0][i].text(0.05, 0.85, "$10^4 c_1 = %.3f \pm %.3f$"%(10000*mc[i,0],10000*mc[i,1]), color='green', ha='left',
va='center', transform=img.axs[0][i].transAxes, fontsize=18)
img.axs[0][i].text(0.05, 0.75, "$10^2 m_2 = %.3f \pm %.3f$"%(100*(mc[i,6]-1),100*mc[i,7]), color='green', ha='left',
va='center', transform=img.axs[0][i].transAxes, fontsize=18)
img.axs[0][i].text(0.05, 0.65, "$10^4 c_2 = %.3f \pm %.3f$"%(10000*mc[i,4],10000*mc[i,5]), color='green', ha='left',
va='center', transform=img.axs[0][i].transAxes, fontsize=18)
img.set_label(0,i,1, "True g")
img.set_label(0,i,0, "Est g")
yu = max(dgs[i][0].max(),dgs[i][1].max())
yd = min(dgs[i][0].min(),dgs[i][1].min())
dy = (yu - yd)*0.3
ax_share = img.share_axis(0,i,1)
# img.axs[1][i].scatter(g1, dgs[i][0], label="$g_1 - \hat{g}_1$")
# img.axs[1][i].scatter(g2, dgs[i][1], label="$g_2 - \hat{g}_2$")
# img.axs[1][i].legend(fontsize=img.legend_size,ncol=2,loc="upper left")
ax_share.scatter(g1, dgs[i][0], edgecolor="C1",facecolor="none",label="$\\Delta g_1 = g_1 - \hat{g}_1$",marker="s",s=pts_s)
ax_share.scatter(g2, dgs[i][1], edgecolor="C4",facecolor="none",label="$\\Delta g_2 = g_2 - \hat{g}_2$",marker="s",s=pts_s)
ax_share.set_ylabel("$10^3\\Delta g$",fontsize=img.xy_lb_size)
ax_share.set_ylim(yd-dy,yu+dy)
img.axs[0][i].plot(x,x,c="grey",ls="dashed")
img.axs[0][i].set_xlim(-0.06,0.06)
img.axs[0][i].set_ylim(-0.06,0.06)
if i== 0:
img.axs[0][i].legend(fontsize=img.legend_size, ncol=2, frameon=False, loc="upper left",
img.axs[ny][nx].scatter(range(1,
len(chi_detect) + 1),
chi_detect,
marker="s",
label="Detected",
facecolor="none",
linewidths=img.plt_line_width,
color="C1",
s=80)
img.axs[ny][nx].plot(range(1,
len(chi_detect) + 1),
chi_detect,
color="C1")
# plot the mean ellipticity of each bin
share_ax = img.share_axis(ny, nx, 1)
ylabel = "|$%s$|" % cmd
share_ax.scatter(range(1,
len(chi_detect) + 1),
ellip_scale,
color="C4",
marker="o",
facecolor="none",
linewidth=img.plt_line_width,
label=ylabel,
s=80)
share_ax.plot(range(1,
len(chi_detect) + 1),
ellip_scale,
color="C4",
linewidth=img.plt_line_width)
